SBIR/STTR Research Award

STTR Phase I: Using Big Data to Support Supply Chain Analytics and Optimization

Award identifier 6a6f1cbb4956260b2c2c475f589af684da4608526ba7e49d8869e3bb99ad32e1Awarding agency National Science Foundation

Award amount

$225,000

Program and phase

STTR · Phase I

Award year

2014

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
OPTIMAL SOLUTIONS INC
Proposal award date
2014-01-01
Contract end date
2014-12-31
UEI
MNRUWLRAW7T6
Solicitation number
Not reported
Topic code
EI

Research abstract

This SBIR Phase I project proposes to demonstrate the feasibility of delivering a radically game-changing Big Data - based Supply Chain Analytics Platform. A complex supply chain, in consumer goods manufacturing and distribution, for example, involves data analysis and decision support in many areas. Today's tools and techniques used in supply chain analytics are too restrictive as they rely on the company's internal factors and are unable to effectively incorporate the increasing volume of readily available, external data. The quality of analytics directly impacts the product quality, cost of fulfillment, customer satisfaction, and ultimately the company's financial health. It is proposed to introduce Big Data concepts including distributed text mining, machine learning, and scalable analytics to support supply chain analytics. The proposed innovation will integrate increasingly available structured and unstructured external data to enhance supply chain decisions. This will enable companies to be more customer-focused, make better decisions, and become more profitable. The key results from this research will include algorithms and methods to pre-process inherently unstructured Big Data into quantitative and qualitative descriptors suitable to be inputs for creating new indicators for decision making. The benefits of better supply chain analytics are clear and significant including better products, better customer service, reduced waste and costs, and increased quality The broader/commercial impact of the proposed innovation is in the area of enhancing product quality and reducing costs for consumer goods companies, increasing the safety of products, and rapid new products introduction into the market based on customer feedback, etc. The proposed research will also significantly lower the technology adoption barriers - both technology-wise and cost-wise barriers to embracing Big Data - while delivering next generation analytics capabilities for businesses and will "democratize" the use of Big Data for companies of all sizes. This is expected to make U.S. companies more competitive resulting in job creation in the U.S. and reducing the outflow of jobs overseas. The potential impact of the proposed research on the business community is significant, and validated in various surveys and studies recently published documenting the benefits of applying Big Data to business.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

11 SBIR/STTR records share this UEI (2012–2025). Reported award amounts total $5,511,428. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Energy, Department of Agriculture, Department of Defense, National Science Foundation

Agency intelligence

National Science Foundation

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